This paper presents results from our experience with CANDID (Comparison Algorithm for Navigating Digital Image Databases), which was designed to facilitate image retrieval by content using a query-by-example methodology. A global signature describing the texture, shape, or color content is first computed for every image stored in a database, and a normalized similarity measure between probability density functions of feature vectors is used to match signatures. This method can be used to retrieve images from a database that are similar to a user-provided example image. Results for three test applications are included.
P.M. Kelly and T.M. Cannon. Experience with CANDID: Comparison Algorithm for Navigating Digital Image Databases. In SPIE Vol. 2368 Proceedings of the 23rd AIPR Workshop on Image and Information Systems: Applications and Opportunities, pages 64-75. Washington, DC. October 12-14, 1994. Los Alamos National Laboratory Technical Report LA-UR-94-3086. [ Abstract | PDF (333 KB) ]
